Quantifying Hail Damage in Crops Using Sentinel-2 Imagery

Remote Sensing

Hema Duddu¹  Thuan Ha²  Steven J. Shirtliffe²  Eric Johnson²  Yanben Shen² 

[1] Agriculture and Agri-Food Canada, Saskatoon, SK S7N 0X2, Canada;Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada;

关键词: hail-to-crop damage;    Sentinel-2;    remote sensing;    precision agriculture;    time-series analysis;    vegetation index;   

DOI  :  10.3390/rs14040951

来源: DOAJ

【 摘 要 】

Hailstorms are a frequent natural weather disaster in the Canadian Prairies that can cause catastrophic damage to field crops. Assessment of damage for insurance claims requires insurance inspectors to visit individual fields and estimate damage on individual plants. This study computes temporal profiles and estimates the severity of hail damage to crops in 54 fields through the temporal analysis of vegetation indices calculated from Sentinel-2 images. The damage estimation accuracy of eight vegetative indices in different temporal analyses of delta index (pre-and post-hail differences) or area under curve (AUC) index (time profiles of index affected by hail) was compared. Hail damage was accurately quantified by using the AUC of 32 days of Normalized Difference Vegetation Indices (NDVI), Normalized Difference Water Index (NDWI), and Plant Senescence Radiation Index (PSRI). These metrics were well correlated with ground estimates of hail damage in canola (r = −0.90, RMSE = 8.24), wheat (r = −0.86, RMSE = 12.27), and lentil (r = 0.80, RMSE = 17.41). Thus, the time-series changes in vegetation indices had a good correlation with ground estimates of hail damage which may allow for more accurate assessment of the extent and severity of hail damage to crop land.

【 授权许可】

Unknown